To investigate online communication as a true human activity, with a long term, comprehensive and holistic approach.
In particular, stressing human growth and quest for meaning in touristic experiences - eTourism.

Elena Marchiori and Lorenzo Cantoni received the Best Paper Award at TTRA Europe Conference 2013

An important achievement for our lab: we received the award for Best Paper at the TTRA Europe Conference (Dublin, Ireland 17-19 April 2013). The research paper is done by Elena Marchiori and Lorenzo Cantoni and is titled “Cues Affecting the Recognition of the Dominant Topic and Sentiment Expressed on Social Media Pages”.

The presented study evaluates users’ agreements on recognizing the dominant topic, and the dominant feeling expressed on social media pages, responding also to a tourism industry need to better understand how to perform effective online communication between tourism players and prospective travellers. Indeed, users might form their idea about a future vacation and/or about a destination from the contents presented online, which are based on relatively impersonal textual resources provided by other users. Moreover, thanks to a heat map analysis technique, asking respondents to pick a spot on an image, the study was able to underline how pages’ features capture the respondents’ attention. Results of this study assess the presence of a common recognition by untrained users of the dominant topic and sentiment expressed on tourism related social media pages, together with several insight regarding web pages’ features. The results obtained encourage future research in the direction to investigate the cues/features from social media pages which might affect the perceived dominant topic and feeling expressed within a page, which in turn might affect the decision making towards a destination.

Here the link to the TTRA Europe book of abstracts.
In the pictures below: Prof. Dr. Kevin Griffin (Chair of the Scientific Committee), Dr. Elena Marchiori, and Prof. Dr. Isabelle Frochot (TTRA Europe President); and a picture of the user test with an example of the heat map analysis.